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Record W7062734804

Video Education and Behavior Contract to Improve Outcomes After Renal Transplantation (VECTOR): A Randomized Controlled Trial

2024· article· en· W7062734804 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdaptive optics and wavefront sensing
Canadian institutionsnot available
Fundersnot available
KeywordsRandomized controlled trialPsychological interventionIntervention (counseling)PharmacyTransplantationKidney transplantationNephrologyKidney transplant
DOInot available

Abstract

fetched live from OpenAlex

Holly Mansell,1 Nicola Rosaasen,2 Jenny Wichart,3 Patricia West-Thielke,4 David Blackburn,1 Juxin Liu,5 Rahul Mainra,6 Ahmed Shoker,6 Brianna Groot,7 Kevin Wen,8 Anita Wong,9 Bita Bateni,10 Cindy Luo,11 Paraag Trivedi12 1College of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, SK, Canada; 2Saskatchewan Transplant Program, Saskatchewan Health Authority, Saskatoon, SK, Canada; 3Department of Pharmacy, Alberta Health Services, Calgary, AB, Canada; 4University of Illinois Health Sciences System, Chicago, IL, USA; 5Department of Mathematics and Statistics, College of Arts and Science, University of Saskatchewan, Saskatoon, SK, Canada; 6Saskatchewan Transplant Program; Department of Medicine, University of Saskatchewan, Saskatoon, SK, Canada; 7Canadian Hub for Applied and Social Research, University of Saskatchewan, Saskatoon, SK, Canada; 8Division of Nephrology and Transplant Immunology, Department of Medicine University of Alberta, Edmonton, AB, Canada; 9Department of Pharmacy, University of Alberta Hospital, Edmonton, AB, Canada; 10St. Paul’s Hospital, and University of British Columbia, Vancouver, BC, Canada; 11Vancouver General Hospital; Faculty of Pharmaceutical Sciences, the University of British Columbia, Vancouver, BC, Canada; 12Transplant Recipient/Patient Advisor, Regina, SK, CanadaCorrespondence: Holly Mansell, College of Pharmacy and Nutrition, Health Sciences Building (E3208), 107 Wiggins Road, Saskatoon, SK, S7N 5E5, Canada, Email holly.mansell@usask.caAbstract: Sub-optimal adherence to immunosuppressant medications reduces graft survival for kidney transplant recipients and adherence-enhancing interventions are resource and time intensive. We performed a multi-center randomized controlled trial to investigate the impact of an electronically delivered intervention on adherence. Of 203 adult kidney transplant recipients who received a de novo kidney transplant n = 173 agreed to participate (intent-to-treat population) and were randomized to the intervention (video education plus behavior contract n = 91) or the control (standard education, n = 82). No significant differences were found between the groups for medication adherence measured by the Basel Assessment of Adherence to Immunosuppressive Medications Scale, intrapatient variability in tacrolimus levels, time in therapeutic range for any immunosuppressant, knowledge, self-efficacy, QOL, or hospitalizations. Among a subgroup of 64 participants randomized to the intervention group who completed a post-intervention questionnaire, two-thirds (67%, n = 43) reported watching at least 80% of the videos and 58% (n = 37) completed the electronic goal setting exercise and adherence contract. An autonomous goal setting exercise and electronic behavioural contract added to standard of care did not improve any outcomes. Our findings reiterate that nonadherence in transplantation is a difficult multifactorial problem that simple solutions will not solve. Trial registration number NCT03540121.Keywords: kidney transplant, solid organ transplant, medication adherence, immunosuppression

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0100.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.060
GPT teacher head0.474
Teacher spread0.414 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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